Visual evoked potentials in multiple sclerosis: P100 latency and visual pathway damage including the lateral geniculate nucleus.

OBJECTIVE: To explore associations of the main component (P100) of visual evoked potentials (VEP) to pre- and postchiasmatic damage in multiple sclerosis (MS). METHODS: 31 patients (median EDSS: 2.5), 13 with previous optic neuritis (ON), and 31 healthy controls had VEP, optical coherence tomography and magnetic resonance imaging. We tested associations of P100-latency to the peripapillary retinal nerve fiber layer (pRNFL), ganglion cell/inner plexiform layers (GCIPL), lateral geniculate nucleus volume (LGN), white matter lesions of the optic radiations (OR-WML), fractional anisotropy of non-lesional optic radiations (NAOR-FA), and to the mean thickness of primary visual cortex (V1). Effect sizes are given as marginal R2 (mR2). RESULTS: P100-latency, pRNFL, GCIPL and LGN in patients differed from controls. Within patients, P100-latency was significantly associated with GCIPL (mR2 = 0.26), and less strongly with OR-WML (mR2 = 0.17), NAOR-FA (mR2 = 0.13) and pRNFL (mR2 = 0.08). In multivariate analysis, GCIPL and NAOR-FA remained significantly associated with P100-latency (mR2 = 0.41). In ON-patients, P100-latency was significantly associated with LGN volume (mR2 = -0.56). CONCLUSIONS: P100-latency is affected by anterior and posterior visual pathway damage. In ON-patients, damage at the synapse-level (LGN) may additionally contribute to latency delay. SIGNIFICANCE: Our findings corroborate post-chiasmatic contributions to the VEP-signal, which may relate to distinct pathophysiological mechanisms in MS.

Short timescale modulation of cortical and cerebellar activity in the early phase of motor sequence learning: an fMRI study.

Motor learning is a multi-stage process, in which the involvement of different brain regions is related to the specific stage. We aimed at characterising short timescale changes of brain activity induced by motor sequence learning. Twenty healthy volunteers performed a serial reaction time task during an MRI session in a 3 T scanner. The task consisted of two conditions: repeated and random, that were compared over the whole fMRI run, as well as within sections, to investigate brain activity modulating related to the learning stage. The whole fMRI run analysis showed a stronger response for the repeated condition in fronto-parietal regions, cerebellum and thalamus. The analysis on sections showed initially increased right cerebellar activity. In the subsequent phase, bilateral cerebellar activity was observed, while no increased activity was seen in the last phase, when the learning was established. At the neocortical level, the repeated condition showed stronger activity at first in fronto-parietal regions bilaterally, then lateralized to the right hemisphere in the last learning phase. This study showed short time scale brain activity modulation in cortical and cerebellar regions with involvement of different brain regions over the learning process not restricted to the motor circuit.

Damage of the lateral geniculate nucleus in MS: Assessing the missing node of the visual pathway.

OBJECTIVE: To study if the thalamic lateral geniculate nucleus (LGN) is affected in multiple sclerosis (MS) due to anterograde degeneration from optic neuritis (ON) or retrograde degeneration from optic radiation (OR) pathology, and if this is relevant for visual function. METHODS: In this cross-sectional study, LGN volume of 34 patients with relapsing-remitting MS and 33 matched healthy controls (HC) was assessed on MRI using atlas-based automated segmentation (MAGeT). ON history, thickness of the ganglion cell-inner plexiform layer (GC-IPL), OR lesion volume, and fractional anisotropy (FA) of normal-appearing OR (NAOR-FA) were assessed as measures of afferent visual pathway damage. Visual function was tested, including low-contrast letter acuity (LCLA) and Hardy-Rand-Rittler (HRR) plates for color vision. RESULTS: LGN volume was reduced in patients vs HC (165.5 ± 45.5 vs 191.4 ± 47.7 mm3, B = -25.89, SE = 5.83, p < 0.001). It was associated with GC-IPL thickness (B = 0.95, SE = 0.33, p = 0.006) and correlated with OR lesion volume (Spearman ρ = -0.53, p = 0.001), and these relationships remained after adjustment for normalized brain volume. There was no association between NAOR-FA and LGN volume (B = -133.28, SE = 88.47, p = 0.137). LGN volume was not associated with LCLA (B = 5.5 × 10-5, SE = 0.03, p = 0.998), but it correlated with HRR color vision (ρ = 0.39, p = 0.032). CONCLUSIONS: LGN volume loss in MS indicates structural damage with potential functional relevance. Our results suggest both anterograde degeneration from the retina and retrograde degeneration from the OR lesions as underlying causes. LGN volume is a promising marker reflecting damage of the visual pathway in MS, with the advantage of individual measurement per patient on conventional MRI.

Subcortical brain segmentation of two dimensional T1-weighted data sets with FMRIB's Integrated Registration and Segmentation Tool (FIRST).

Brain atrophy has been identified as an important contributing factor to the development of disability in multiple sclerosis (MS). In this respect, more and more interest is focussing on the role of deep grey matter (DGM) areas. Novel data analysis pipelines are available for the automatic segmentation of DGM using three-dimensional (3D) MRI data. However, in clinical trials, often no such high-resolution data are acquired and hence no conclusions regarding the impact of new treatments on DGM atrophy were possible so far. In this work, we used FMRIB's Integrated Registration and Segmentation Tool (FIRST) to evaluate the possibility of segmenting DGM structures using standard two-dimensional (2D) T1-weighted MRI. In a cohort of 70 MS patients, both 2D and 3D T1-weighted data were acquired. The thalamus, putamen, pallidum, nucleus accumbens, and caudate nucleus were bilaterally segmented using FIRST. Volumes were calculated for each structure and for the sum of basal ganglia (BG) as well as for the total DGM. The accuracy and reliability of the 2D data segmentation were compared with the respective results of 3D segmentations using volume difference, volume overlap and intra-class correlation coefficients (ICCs). The mean differences for the individual substructures were between 1.3% (putamen) and -25.2% (nucleus accumbens). The respective values for the BG were -2.7% and for DGM 1.3%. Mean volume overlap was between 89.1% (thalamus) and 61.5% (nucleus accumbens); BG: 84.1%; DGM: 86.3%. Regarding ICC, all structures showed good agreement with the exception of the nucleus accumbens. The results of the segmentation were additionally validated through expert manual delineation of the caudate nucleus and putamen in a subset of the 3D data. In conclusion, we demonstrate that subcortical segmentation of 2D data are feasible using FIRST. The larger subcortical GM structures can be segmented with high consistency. This forms the basis for the application of FIRST in large 2D MRI data sets of clinical trials in order to determine the impact of therapeutic interventions on DGM atrophy in MS.